This research introduces Fortified-Edge 2.0, a novel authentication framework that addresses critical security and privacy challenges in Physically Unclonable Function (PUF)-based systems for collaborative edge computing (CEC). Unlike conventional methods that transmit full binary Challenge–Response Pairs (CRPs) and risk exposing sensitive data, Fortified-Edge 2.0 employs a machine-learning-driven feature-abstraction technique to extract and utilize only essential characteristics of CRPs, obfuscating the raw binary sequences. These feature vectors are then processed using lightweight cryptographic primitives, including ECDSA, to enable secure authentication without exposing the original CRP. This eliminates the need to transmit sensitive binary data, reducing the attack surface and bandwidth usage. The proposed method demonstrates strong resilience against modeling attacks, replay attacks, and side-channel threats while maintaining the inherent efficiency and low power requirements of PUFs. By integrating PUF unpredictability with ML adaptability, this research delivers a scalable, secure, and resource-efficient solution for next-generation authentication in edge environments.
Handover management is a fundamental process in modern mobile networks, ensuring service continuity under user mobility. However, the relationship between network conditions and handover behavior remains insufficiently understood under real-world measurement conditions. This stud…
Emerging edge devices are transforming the Internet of Things (IoT) by enabling more responsive and efficient interactions between physical objects and digital networks. These devices support diverse applications, from health-monitoring wearables to environmental sensors, by movi…
The rise in internet users has brought with it the impending threat of cybercrime as the Internet of Things (IoT) increases and the introduction of 5G technologies continues to transform our digital world. It is now essential to protect communication networks from illegal intrusi…
Human–machine interaction (HMI) refers to systems enabling communication between machines and humans. Systems for human–machine interfaces have advanced significantly in terms of materials, device design, and production methods. Energy supply units, logic circuits, sensors, and d…
Urban agriculture presents unique challenges, particularly in the context of microclimate monitoring, which is increasingly important in food production. This paper explores the application of convolutional neural networks (CNNs) to forecast key sensor measurements from thermal i…
Wireless sensor networks (WSNs) have become a critical component of modern Internet of Things (IoT) infrastructures; however, their constrained resources and distributed deployment expose them to various cyber threats. In this work, we present a machine learning-driven intrusion…